{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "b1f1e9b3-8c54-495c-8b8a-8762f72299eb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost after iteration 0: 0.771749\n",
      "Cost after iteration 100: 0.677781\n",
      "Cost after iteration 200: 0.661606\n",
      "Cost after iteration 300: 0.639080\n",
      "Cost after iteration 400: 0.614008\n",
      "Cost after iteration 500: 0.585342\n",
      "Cost after iteration 600: 0.562571\n",
      "Cost after iteration 700: 0.514817\n",
      "Cost after iteration 800: 0.465298\n",
      "Cost after iteration 900: 0.432272\n",
      "Cost after iteration 1000: 0.412280\n",
      "Cost after iteration 1100: 0.354945\n",
      "Cost after iteration 1200: 0.317725\n",
      "Cost after iteration 1300: 0.291652\n",
      "Cost after iteration 1400: 0.271591\n",
      "Cost after iteration 1500: 0.246205\n",
      "Cost after iteration 1600: 0.230090\n",
      "Cost after iteration 1700: 0.207156\n",
      "Cost after iteration 1800: 0.193781\n",
      "Cost after iteration 1900: 0.195979\n",
      "Cost after iteration 2000: 0.172805\n",
      "Cost after iteration 2100: 0.162932\n",
      "Cost after iteration 2200: 0.154658\n",
      "Cost after iteration 2300: 0.147815\n",
      "Cost after iteration 2400: 0.145527\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "查看猫图中的： cat11\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "无猫\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import h5py\n",
    "import matplotlib.pyplot as plt\n",
    "import scipy   \n",
    "from PIL import Image\n",
    "from scipy import ndimage\n",
    "from lr_utils import load_dataset\n",
    "\n",
    "# from dnn_app_utils_v2 import *\n",
    "\n",
    "num_px = 64\n",
    "\n",
    "%matplotlib inline\n",
    "plt.rcParams['figure.figsize'] = (5.0, 4.0) # set default size of plots\n",
    "plt.rcParams['image.interpolation'] = 'nearest'\n",
    "plt.rcParams['image.cmap'] = 'gray'\n",
    "\n",
    "\n",
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "\n",
    "    \n",
    "\n",
    "def sigmoid(Z):\n",
    "    \"\"\"\n",
    "    Implements the sigmoid activation in numpy\n",
    "    \n",
    "    Arguments:\n",
    "    Z -- numpy array of any shape\n",
    "    \n",
    "    Returns:\n",
    "    A -- output of sigmoid(z), same shape as Z\n",
    "    cache -- returns Z as well, useful during backpropagation\n",
    "    \"\"\"\n",
    "    \n",
    "    A = 1/(1+np.exp(-Z))\n",
    "    cache = Z\n",
    "    \n",
    "    return A, cache\n",
    "\n",
    "def relu(Z):\n",
    "    \"\"\"\n",
    "    Implement the RELU function.\n",
    "\n",
    "    Arguments:\n",
    "    Z -- Output of the linear layer, of any shape\n",
    "\n",
    "    Returns:\n",
    "    A -- Post-activation parameter, of the same shape as Z\n",
    "    cache -- a python dictionary containing \"A\" ; stored for computing the backward pass efficiently\n",
    "    \"\"\"\n",
    "    \n",
    "    A = np.maximum(0,Z)\n",
    "    \n",
    "    assert(A.shape == Z.shape)\n",
    "    \n",
    "    cache = Z \n",
    "    return A, cache\n",
    "\n",
    "\n",
    "def relu_backward(dA, cache):\n",
    "    \"\"\"\n",
    "    Implement the backward propagation for a single RELU unit.\n",
    "\n",
    "    Arguments:\n",
    "    dA -- post-activation gradient, of any shape\n",
    "    cache -- 'Z' where we store for computing backward propagation efficiently\n",
    "\n",
    "    Returns:\n",
    "    dZ -- Gradient of the cost with respect to Z\n",
    "    \"\"\"\n",
    "    \n",
    "    Z = cache\n",
    "    dZ = np.array(dA, copy=True) # just converting dz to a correct object.\n",
    "    \n",
    "    # When z <= 0, you should set dz to 0 as well. \n",
    "    dZ[Z <= 0] = 0\n",
    "    \n",
    "    assert (dZ.shape == Z.shape)\n",
    "    \n",
    "    return dZ\n",
    "\n",
    "def sigmoid_backward(dA, cache):\n",
    "    \"\"\"\n",
    "    Implement the backward propagation for a single SIGMOID unit.\n",
    "\n",
    "    Arguments:\n",
    "    dA -- post-activation gradient, of any shape\n",
    "    cache -- 'Z' where we store for computing backward propagation efficiently\n",
    "\n",
    "    Returns:\n",
    "    dZ -- Gradient of the cost with respect to Z\n",
    "    \"\"\"\n",
    "    \n",
    "    Z = cache\n",
    "    \n",
    "    s = 1/(1+np.exp(-Z))\n",
    "    dZ = dA * s * (1-s)\n",
    "    \n",
    "    assert (dZ.shape == Z.shape)\n",
    "    \n",
    "    return dZ\n",
    "\n",
    "\n",
    "def load_data():\n",
    "    train_dataset = h5py.File('datasets/train_catvnoncat.h5', \"r\")\n",
    "    train_set_x_orig = np.array(train_dataset[\"train_set_x\"][:]) # your train set features\n",
    "    train_set_y_orig = np.array(train_dataset[\"train_set_y\"][:]) # your train set labels\n",
    "\n",
    "    test_dataset = h5py.File('datasets/test_catvnoncat.h5', \"r\")\n",
    "    test_set_x_orig = np.array(test_dataset[\"test_set_x\"][:]) # your test set features\n",
    "    test_set_y_orig = np.array(test_dataset[\"test_set_y\"][:]) # your test set labels\n",
    "\n",
    "    classes = np.array(test_dataset[\"list_classes\"][:]) # the list of classes\n",
    "    \n",
    "    train_set_y_orig = train_set_y_orig.reshape((1, train_set_y_orig.shape[0]))\n",
    "    test_set_y_orig = test_set_y_orig.reshape((1, test_set_y_orig.shape[0]))\n",
    "    \n",
    "    return train_set_x_orig, train_set_y_orig, test_set_x_orig, test_set_y_orig, classes\n",
    " # =================================================================================================\n",
    "\n",
    "\n",
    "def initialize_parameters_deep(layer_dims):\n",
    "    \"\"\"\n",
    "    Arguments:\n",
    "    layer_dims -- python array (list) containing the dimensions of each layer in our network\n",
    "    \n",
    "    Returns:\n",
    "    parameters -- python dictionary containing your parameters \"W1\", \"b1\", ..., \"WL\", \"bL\":\n",
    "                    Wl -- weight matrix of shape (layer_dims[l], layer_dims[l-1])\n",
    "                    bl -- bias vector of shape (layer_dims[l], 1)\n",
    "    \"\"\"\n",
    "    \n",
    "    np.random.seed(1)\n",
    "    parameters = {}\n",
    "    L = len(layer_dims)            # number of layers in the network\n",
    "\n",
    "    for l in range(1, L):\n",
    "        parameters['W' + str(l)] = np.random.randn(layer_dims[l], layer_dims[l-1]) / np.sqrt(layer_dims[l-1]) #*0.01\n",
    "        parameters['b' + str(l)] = np.zeros((layer_dims[l], 1))\n",
    "        \n",
    "        assert(parameters['W' + str(l)].shape == (layer_dims[l], layer_dims[l-1]))\n",
    "        assert(parameters['b' + str(l)].shape == (layer_dims[l], 1))\n",
    "\n",
    "        \n",
    "    return parameters\n",
    "\n",
    "def linear_forward(A, W, b):\n",
    "    \"\"\"\n",
    "    Implement the linear part of a layer's forward propagation.\n",
    "\n",
    "    Arguments:\n",
    "    A -- activations from previous layer (or input data): (size of previous layer, number of examples)\n",
    "    W -- weights matrix: numpy array of shape (size of current layer, size of previous layer)\n",
    "    b -- bias vector, numpy array of shape (size of the current layer, 1)\n",
    "\n",
    "    Returns:\n",
    "    Z -- the input of the activation function, also called pre-activation parameter \n",
    "    cache -- a python dictionary containing \"A\", \"W\" and \"b\" ; stored for computing the backward pass efficiently\n",
    "    \"\"\"\n",
    "    \n",
    "    Z = W.dot(A) + b\n",
    "    \n",
    "    assert(Z.shape == (W.shape[0], A.shape[1]))\n",
    "    cache = (A, W, b)\n",
    "    \n",
    "    return Z, cache\n",
    "\n",
    "def linear_activation_forward(A_prev, W, b, activation):\n",
    "    \"\"\"\n",
    "    Implement the forward propagation for the LINEAR->ACTIVATION layer\n",
    "\n",
    "    Arguments:\n",
    "    A_prev -- activations from previous layer (or input data): (size of previous layer, number of examples)\n",
    "    W -- weights matrix: numpy array of shape (size of current layer, size of previous layer)\n",
    "    b -- bias vector, numpy array of shape (size of the current layer, 1)\n",
    "    activation -- the activation to be used in this layer, stored as a text string: \"sigmoid\" or \"relu\"\n",
    "\n",
    "    Returns:\n",
    "    A -- the output of the activation function, also called the post-activation value \n",
    "    cache -- a python dictionary containing \"linear_cache\" and \"activation_cache\";\n",
    "             stored for computing the backward pass efficiently\n",
    "    \"\"\"\n",
    "    \n",
    "    if activation == \"sigmoid\":\n",
    "        # Inputs: \"A_prev, W, b\". Outputs: \"A, activation_cache\".\n",
    "        Z, linear_cache = linear_forward(A_prev, W, b)\n",
    "        A, activation_cache = sigmoid(Z)\n",
    "    \n",
    "    elif activation == \"relu\":\n",
    "        # Inputs: \"A_prev, W, b\". Outputs: \"A, activation_cache\".\n",
    "        Z, linear_cache = linear_forward(A_prev, W, b)\n",
    "        A, activation_cache = relu(Z)\n",
    "    \n",
    "    assert (A.shape == (W.shape[0], A_prev.shape[1]))\n",
    "    cache = (linear_cache, activation_cache)\n",
    "\n",
    "    return A, cache\n",
    "\n",
    "def L_model_forward(X, parameters):\n",
    "    \"\"\"\n",
    "    Implement forward propagation for the [LINEAR->RELU]*(L-1)->LINEAR->SIGMOID computation\n",
    "    \n",
    "    Arguments:\n",
    "    X -- data, numpy array of shape (input size, number of examples)\n",
    "    parameters -- output of initialize_parameters_deep()\n",
    "    \n",
    "    Returns:\n",
    "    AL -- last post-activation value\n",
    "    caches -- list of caches containing:\n",
    "                every cache of linear_relu_forward() (there are L-1 of them, indexed from 0 to L-2)\n",
    "                the cache of linear_sigmoid_forward() (there is one, indexed L-1)\n",
    "    \"\"\"\n",
    "\n",
    "    caches = []\n",
    "    A = X\n",
    "    L = len(parameters) // 2                  # number of layers in the neural network\n",
    "    \n",
    "    # Implement [LINEAR -> RELU]*(L-1). Add \"cache\" to the \"caches\" list.\n",
    "    for l in range(1, L):\n",
    "        A_prev = A \n",
    "        A, cache = linear_activation_forward(A_prev, parameters['W' + str(l)], parameters['b' + str(l)], activation = \"relu\")\n",
    "        caches.append(cache)\n",
    "    \n",
    "    # Implement LINEAR -> SIGMOID. Add \"cache\" to the \"caches\" list.\n",
    "    AL, cache = linear_activation_forward(A, parameters['W' + str(L)], parameters['b' + str(L)], activation = \"sigmoid\")\n",
    "    caches.append(cache)\n",
    "    \n",
    "    assert(AL.shape == (1,X.shape[1]))\n",
    "            \n",
    "    return AL, caches\n",
    "\n",
    "def compute_cost(AL, Y):\n",
    "    \"\"\"\n",
    "    Implement the cost function defined by equation (7).\n",
    "\n",
    "    Arguments:\n",
    "    AL -- probability vector corresponding to your label predictions, shape (1, number of examples)\n",
    "    Y -- true \"label\" vector (for example: containing 0 if non-cat, 1 if cat), shape (1, number of examples)\n",
    "\n",
    "    Returns:\n",
    "    cost -- cross-entropy cost\n",
    "    \"\"\"\n",
    "    \n",
    "    m = Y.shape[1]\n",
    "\n",
    "    # Compute loss from aL and y.\n",
    "    cost = (1./m) * (-np.dot(Y,np.log(AL).T) - np.dot(1-Y, np.log(1-AL).T))\n",
    "    \n",
    "    cost = np.squeeze(cost)      # To make sure your cost's shape is what we expect (e.g. this turns [[17]] into 17).\n",
    "    assert(cost.shape == ())\n",
    "    \n",
    "    return cost\n",
    "\n",
    "def linear_backward(dZ, cache):\n",
    "    \"\"\"\n",
    "    Implement the linear portion of backward propagation for a single layer (layer l)\n",
    "\n",
    "    Arguments:\n",
    "    dZ -- Gradient of the cost with respect to the linear output (of current layer l)\n",
    "    cache -- tuple of values (A_prev, W, b) coming from the forward propagation in the current layer\n",
    "\n",
    "    Returns:\n",
    "    dA_prev -- Gradient of the cost with respect to the activation (of the previous layer l-1), same shape as A_prev\n",
    "    dW -- Gradient of the cost with respect to W (current layer l), same shape as W\n",
    "    db -- Gradient of the cost with respect to b (current layer l), same shape as b\n",
    "    \"\"\"\n",
    "    A_prev, W, b = cache\n",
    "    m = A_prev.shape[1]\n",
    "\n",
    "    dW = 1./m * np.dot(dZ,A_prev.T)\n",
    "    db = 1./m * np.sum(dZ, axis = 1, keepdims = True)\n",
    "    dA_prev = np.dot(W.T,dZ)\n",
    "    \n",
    "    assert (dA_prev.shape == A_prev.shape)\n",
    "    assert (dW.shape == W.shape)\n",
    "    assert (db.shape == b.shape)\n",
    "    \n",
    "    return dA_prev, dW, db\n",
    "\n",
    "def linear_activation_backward(dA, cache, activation):\n",
    "    \"\"\"\n",
    "    Implement the backward propagation for the LINEAR->ACTIVATION layer.\n",
    "    \n",
    "    Arguments:\n",
    "    dA -- post-activation gradient for current layer l \n",
    "    cache -- tuple of values (linear_cache, activation_cache) we store for computing backward propagation efficiently\n",
    "    activation -- the activation to be used in this layer, stored as a text string: \"sigmoid\" or \"relu\"\n",
    "    \n",
    "    Returns:\n",
    "    dA_prev -- Gradient of the cost with respect to the activation (of the previous layer l-1), same shape as A_prev\n",
    "    dW -- Gradient of the cost with respect to W (current layer l), same shape as W\n",
    "    db -- Gradient of the cost with respect to b (current layer l), same shape as b\n",
    "    \"\"\"\n",
    "    linear_cache, activation_cache = cache\n",
    "    \n",
    "    if activation == \"relu\":\n",
    "        dZ = relu_backward(dA, activation_cache)\n",
    "        dA_prev, dW, db = linear_backward(dZ, linear_cache)\n",
    "        \n",
    "    elif activation == \"sigmoid\":\n",
    "        dZ = sigmoid_backward(dA, activation_cache)\n",
    "        dA_prev, dW, db = linear_backward(dZ, linear_cache)\n",
    "    \n",
    "    return dA_prev, dW, db\n",
    "\n",
    "def L_model_backward(AL, Y, caches):\n",
    "    \"\"\"\n",
    "    Implement the backward propagation for the [LINEAR->RELU] * (L-1) -> LINEAR -> SIGMOID group\n",
    "    \n",
    "    Arguments:\n",
    "    AL -- probability vector, output of the forward propagation (L_model_forward())\n",
    "    Y -- true \"label\" vector (containing 0 if non-cat, 1 if cat)\n",
    "    caches -- list of caches containing:\n",
    "                every cache of linear_activation_forward() with \"relu\" (there are (L-1) or them, indexes from 0 to L-2)\n",
    "                the cache of linear_activation_forward() with \"sigmoid\" (there is one, index L-1)\n",
    "    \n",
    "    Returns:\n",
    "    grads -- A dictionary with the gradients\n",
    "             grads[\"dA\" + str(l)] = ... \n",
    "             grads[\"dW\" + str(l)] = ...\n",
    "             grads[\"db\" + str(l)] = ... \n",
    "    \"\"\"\n",
    "    grads = {}\n",
    "    L = len(caches) # the number of layers\n",
    "    m = AL.shape[1]\n",
    "    Y = Y.reshape(AL.shape) # after this line, Y is the same shape as AL\n",
    "    \n",
    "    # Initializing the backpropagation\n",
    "    dAL = - (np.divide(Y, AL) - np.divide(1 - Y, 1 - AL))\n",
    "    \n",
    "    # Lth layer (SIGMOID -> LINEAR) gradients. Inputs: \"AL, Y, caches\". Outputs: \"grads[\"dAL\"], grads[\"dWL\"], grads[\"dbL\"]\n",
    "    current_cache = caches[L-1]\n",
    "    grads[\"dA\" + str(L)], grads[\"dW\" + str(L)], grads[\"db\" + str(L)] = linear_activation_backward(dAL, current_cache, activation = \"sigmoid\")\n",
    "    \n",
    "    for l in reversed(range(L-1)):\n",
    "        # lth layer: (RELU -> LINEAR) gradients.\n",
    "        current_cache = caches[l]\n",
    "        dA_prev_temp, dW_temp, db_temp = linear_activation_backward(grads[\"dA\" + str(l + 2)], current_cache, activation = \"relu\")\n",
    "        grads[\"dA\" + str(l + 1)] = dA_prev_temp\n",
    "        grads[\"dW\" + str(l + 1)] = dW_temp\n",
    "        grads[\"db\" + str(l + 1)] = db_temp\n",
    "\n",
    "    return grads\n",
    "\n",
    "def update_parameters(parameters, grads, learning_rate):\n",
    "    \"\"\"\n",
    "    Update parameters using gradient descent\n",
    "    \n",
    "    Arguments:\n",
    "    parameters -- python dictionary containing your parameters \n",
    "    grads -- python dictionary containing your gradients, output of L_model_backward\n",
    "    \n",
    "    Returns:\n",
    "    parameters -- python dictionary containing your updated parameters \n",
    "                  parameters[\"W\" + str(l)] = ... \n",
    "                  parameters[\"b\" + str(l)] = ...\n",
    "    \"\"\"\n",
    "    \n",
    "    L = len(parameters) // 2 # number of layers in the neural network\n",
    "\n",
    "    # Update rule for each parameter. Use a for loop.\n",
    "    for l in range(L):\n",
    "        parameters[\"W\" + str(l+1)] = parameters[\"W\" + str(l+1)] - learning_rate * grads[\"dW\" + str(l+1)]\n",
    "        parameters[\"b\" + str(l+1)] = parameters[\"b\" + str(l+1)] - learning_rate * grads[\"db\" + str(l+1)]\n",
    "        \n",
    "    return parameters\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "def sigmoid_to_binary(AL):  \n",
    "\n",
    "    m = AL.shape[1]\n",
    "    Y = np.zeros((1,m))\n",
    "    \n",
    "    for i in range(m):\n",
    "        if AL[0,i]>=0.5:\n",
    "            Y[0,i] = 1\n",
    "        else:\n",
    "            Y[0,i] = 0\n",
    "    return Y\n",
    "\n",
    "\n",
    "train_x_orig, train_y, test_x_orig, test_y, classes = load_data()\n",
    "\n",
    "# Reshape the training and test examples \n",
    "train_x_flatten = train_x_orig.reshape(train_x_orig.shape[0], -1).T   # The \"-1\" makes reshape flatten the remaining dimensions\n",
    "test_x_flatten = test_x_orig.reshape(test_x_orig.shape[0], -1).T\n",
    "\n",
    "# Standardize data to have feature values between 0 and 1.\n",
    "train_x = train_x_flatten/255.\n",
    "test_x = test_x_flatten/255.\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "layers_dims = [12288, 20, 7, 5, 1]     #  5-layer model\n",
    "\n",
    "\n",
    "\n",
    "def L_layer_model(X, Y, layers_dims, learning_rate = 0.005, num_iterations = 3000, print_cost=True):  #lr was 0.009\n",
    "    \"\"\"\n",
    "    Implements a L-layer neural network: [LINEAR->RELU]*(L-1)->LINEAR->SIGMOID.\n",
    "    \n",
    "    Arguments:\n",
    "    X -- data, numpy array of shape (number of examples, num_px * num_px * 3)\n",
    "    Y -- true \"label\" vector (containing 0 if cat, 1 if non-cat), of shape (1, number of examples)\n",
    "    layers_dims -- list containing the input size and each layer size, of length (number of layers + 1).\n",
    "    learning_rate -- learning rate of the gradient descent update rule\n",
    "    num_iterations -- number of iterations of the optimization loop\n",
    "    print_cost -- if True, it prints the cost every 100 steps\n",
    "    \n",
    "    Returns:\n",
    "    parameters -- parameters learnt by the model. They can then be used to predict.\n",
    "    \"\"\"\n",
    "\n",
    "    np.random.seed(1)\n",
    "    costs = []                         # keep track of cost\n",
    "    \n",
    "    # Parameters initialization.\n",
    "    ### START CODE HERE ###\n",
    "    parameters = initialize_parameters_deep(layers_dims)\n",
    "    ### END CODE HERE ###\n",
    "    \n",
    "    # Loop (gradient descent)\n",
    "    for i in range(num_iterations):\n",
    "\n",
    "        # Forward propagation: [LINEAR -> RELU]*(L-1) -> LINEAR -> SIGMOID.\n",
    "        ### START CODE HERE ### (≈ 1 line of code)\n",
    "        AL, caches =  L_model_forward(X, parameters)\n",
    "        ### END CODE HERE ###\n",
    "        \n",
    "        # Compute cost.\n",
    "        ### START CODE HERE ### (≈ 1 line of code)\n",
    "        cost = compute_cost(AL, Y)\n",
    "        ### END CODE HERE ###\n",
    "    \n",
    "        # Backward propagation.\n",
    "        ### START CODE HERE ### (≈ 1 line of code)\n",
    "        grads = L_model_backward(AL, Y, caches)\n",
    "        ### END CODE HERE ###\n",
    " \n",
    "        # Update parameters.\n",
    "        ### START CODE HERE ### (≈ 1 line of code)\n",
    "        parameters = update_parameters(parameters, grads, learning_rate=0.005)\n",
    "        ### END CODE HERE ###\n",
    "                \n",
    "        # Print the cost every 100 training example\n",
    "        if print_cost and i % 100 == 0:\n",
    "            print (\"Cost after iteration %i: %f\" %(i, cost))\n",
    "        if print_cost and i % 100 == 0:\n",
    "            costs.append(cost)\n",
    "            \n",
    "    # plot the cost\n",
    "    plt.plot(np.squeeze(costs))\n",
    "    plt.ylabel('cost')\n",
    "    plt.xlabel('iterations (per tens)')\n",
    "    plt.title(\"Learning rate =\" + str(learning_rate))\n",
    "    plt.show()\n",
    "    \n",
    "    return parameters\n",
    "\n",
    "\n",
    "parameters = L_layer_model(train_x, train_y,layers_dims, num_iterations = 2500, print_cost=True)\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "# my_image = input('导入图片名称：')\n",
    "my_image = input('查看猫图中的：')\n",
    "    \n",
    "fname = \"猫图/\" + my_image + '.jpg'\n",
    "    \n",
    "image = Image.open(fname)  \n",
    "image_resized = image.resize((num_px, num_px))  \n",
    "my_image = np.array(image_resized).reshape((1,num_px*num_px*3)).astype(np.float32).T\n",
    "\n",
    "\n",
    "\n",
    "## 对判断样本标准化，否则会使  sigmoid 函数的结果溢出\n",
    "my_image /= 255 \n",
    "\n",
    "## 判断\n",
    "plt.imshow(image) # 显示图片\n",
    "\n",
    "\n",
    "AL,caches = L_model_forward(my_image, parameters)\n",
    "Y = sigmoid_to_binary(AL)\n",
    "if Y[0,0] == 1:\n",
    "    print('有猫')\n",
    "else:\n",
    "    print('无猫')"
   ]
  }
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